Overview
Open-source vector database for billion-scale workloads. Milvus sits in the AI infrastructure layer that other products rely on for serving, vector search, embeddings, or training.
What you get
Tools in this category handle the unglamorous-but-load-bearing parts of running AI in production: hosting open models, semantic search, retrieval pipelines, embeddings, evaluation, and observability. Expect SDKs, low-latency APIs, and pricing that maps to compute, storage, or queries.
Where it fits in your stack
They sit between your application code and the foundation-model providers. Teams often combine several (a vector database for retrieval, an inference host for open-source models, an evaluation/observability layer) to keep AI features reliable as they scale.
Who it’s for
Milvus is aimed primarily at builders looking for a focused tool in this space. When evaluating, look at latency, recall, regional availability, cost at the volume you actually expect, and how cleanly the tool integrates with your existing observability and CI.
Pricing & licensing
Most products at this layer price by tokens, requests, or compute time, with free credits to evaluate and tiered rate limits as you scale. Check Milvus’s pricing page for current rates, and budget for both inference cost and the supporting infrastructure (caching, observability, evaluation) you’ll add around it.